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A Traffic Analysis on Serverless Computing Based on the Example of a File Upload Stream on AWS Lambda

Muller, Lisa; Chrysoulas, Christos; Pitropakis, Nikolaos; Barclay, Peter J.

Authors

Lisa Muller



Abstract

The shift towards microservisation which can be observed in recent developments of the cloud landscape for applications has led towards the emergence of the Function as a Service (FaaS) concept, also called Serverless. This term describes the event-driven, reactive programming paradigm of functional components in container instances, which are scaled, deployed, executed and billed by the cloud provider on demand. However, increasing reports of issues of Serverless services have shown significant obscurity regarding its reliability. In particular, developers and especially system administrators struggle with latency compliance. In this paper, following a systematic literature review, the performance indicators influencing traffic and the effective delivery of the provider’s underlying infrastructure are determined by carrying out empirical measurements based on the example of a File Upload Stream on Amazon’s Web Service Cloud. This popular example was used as an experimental baseline in this study, based on different incoming request rates. Different parameters were used to monitor and evaluate changes through the function’s logs. It has been found that the so-called Cold-Start, meaning the time to provide a new instance, can increase the Round-Trip-Time by 15%, on average. Cold-Start happens after an instance has not been called for around 15 min, or after around 2 h have passed, which marks the end of the instance’s lifetime. The research shows how the numbers have changed in comparison to earlier related work, as Serverless is a fast-growing field of development. Furthermore, emphasis is given towards future research to improve the technology, algorithms, and support for developers.

Citation

Muller, L., Chrysoulas, C., Pitropakis, N., & Barclay, P. J. (2020). A Traffic Analysis on Serverless Computing Based on the Example of a File Upload Stream on AWS Lambda. Big Data and Cognitive Computing, 4(4), Article 38. https://doi.org/10.3390/bdcc4040038

Journal Article Type Article
Acceptance Date Dec 7, 2020
Online Publication Date Dec 10, 2020
Publication Date 2020-12
Deposit Date Dec 12, 2020
Publicly Available Date Mar 29, 2024
Journal Big Data and Cognitive Computing
Print ISSN 2504-2289
Publisher MDPI
Peer Reviewed Peer Reviewed
Volume 4
Issue 4
Article Number 38
DOI https://doi.org/10.3390/bdcc4040038
Keywords serverless computing; cloud computing; AWS Lambda; traffic analysis; FaaS; performance
Public URL http://researchrepository.napier.ac.uk/Output/2710837

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Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/

Copyright Statement
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.




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